Certificate Programs

Certificate Programs

General Information

• For the 2016-2017 academic year the tuition is $600/credit hour. Book costs are in addition to the tuition.
• Certificate programs are not eligible for federal financial aid.
• If you want to pursue a graduate degree after completing a certificate, the certificate courses can be used towards a graduate degree program.
• Applications for the certificate programs are reviewed on a continual basis.

Choose a Program

Supply Chain Management

Supply chain management professionals are involved in all business processes from raw materials extraction to consumer purchase, ensuring the right product is in the hands of the right consumer at the right time. This program provides exposure to the key concepts, tools and technologies needed for a successful career in supply chain mangement. The certificate coursework covers a wide array of important topics, including strategic supply chain design, supply chain planning and forecasting, sourcing and procurement, logistics, distribution and inventory mangement and lean management principles.

Steps to Enroll Now in the Supply Chain Management Certificate Program

Complete an application for admission
• Please note that under the Admission Objective you select “Non-Degree, Graduate Certificate Objective” and then select “Graduate Certificate in Supply Chain Management Systems.”
• You will receive an email prompting you to complete your department application in GAMES.
• If you would like to apply to the MBA program and earn a specialization in supply chain management, please refer to the MBA admission requirements and application procedures.

Registration codes for the certificate courses will be sent out from the Graduate Programs office approximately 30 days prior to the term start date.

Supply Chain Management Program Course Listing and Requirements

Successful completion of GRBA 815 Supply
Chain Management Strategies
plus three other courses with at least a C or better in each class is required.
Classes can be taken
pass/no pass, but pass is defined as C or better for this purpose.

Business Analytics

The business analytics certificate program is designed to assist students in developing the ability to solve practical business problems by applying analytical techniques to data. Business Analytics (GRBA 851) and Econometrics (ECON 817) provide the necessary background in statistical and analytical methods. Those courses offer an overview of key statistical concepts and techniques, including multivariate methods, while incorporating hands-on data analysis. The remaining two courses, Strategic Database Marketing (MRKT 850) and Data Mining (SCMA 853) are hands-on with a focus on problem-solving. The examples discussed in these two courses will demonstrate how to apply specific statistical and analytic techniques to a variety of practical problems. The courses in this certificate program will expose students to software and programming languages used for statistics and data analysis in industry.

Develop a broad understanding of important topics in business analytics and how they can be used to support
decision-making in business, government, education and agriculture

Learn to use data to explore past performance and improve future performance

Steps to Enroll Now for Business Analytics Certificate Program

Complete an application for admission
• Please note that under the Admission Objective you select “Non-Degree, Graduate Certificate Objective” and then select “Graduate Certificate in Business Analytics.”
• You will receive an email prompting you to complete your department application in GAMES.
• If you would like to apply to the MBA program and earn a specialization in supply chain management, please refer to the MBA admission requirements and application procedures.

Ensure that you have met the pre-requisites of a bachelor's degree and an introductory statistics course with a grade of
C or better. If you have not taken statistics, you can take UNL’s ECON215 or STAT218. For students who are not in the Lincoln
area, an equivalent course can be taken at a college or university in your local area. Refer to
UNL's transfer equivalency webpage to
make sure the course you take has been evaluated as being equivalent to
UNL’s ECON215 or STAT218. Doing well in basic statistics is important to your success in the
business analytics program.

Registration codes for the certificate courses will be sent out from the Graduate Programs office approximately 30 days prior to the term start date.

Required Courses to Complete Business Analytics Program

GRBA 851 is required as the first course in the program, as it explains what business analytics is, why it is so important and how to use it.
It also includes an overview of the principles, concepts and applications of business analytics.
Upon completion of GRBA 851, the other three courses may be taken in any sequence.

GRBA 851 Business Analytics (this course must be completed first)

Basic statistical understanding, including performing statistical tests, up through ordinary least squares regression. Students that did not do well in a fairly recent basic statistics course may struggle with the business analytics curriculum.

ECON 817 Introductory Econometrics

Know how to construct and interpret tabular summaries such as frequency and
relative frequency distributions, cumulative frequency and cumulative relative frequency distributions.

Know how to construct and interpret graphical summaries such as histogram,
ogive, stem and leaf and box plot.

Be able to compute and interpret a variety of measures of location.

Understand the concept of deviations from the mean and their role in measuring variation.

Be able to compute and interpret variance, standard deviation and coefficient of variation.

Understand skewness as a measure of distribution shape.

Understand z scores and their role as a measure of relative location.

Know how to determine percentages of the data within a specified number of standard deviations from the mean.

Basic probability:

Have an appreciation of the role that probability information plays in decision making processes.

Know the three methods commonly used for assigning probabilities and understand when they should be used.

Know how to use the laws that are available for computing probabilities of events.

Random variables:

Understand the concepts of a random variable and a probability distribution.

Be able to compute and interpret the expected value, variance and standard deviation for a discrete random variable.

Be able to compute and work with probabilities involving binomial, hypergeometric and Poisson probability distributions.

Know how to compute probability values, expected value and variance for a continuous uniform probability distribution.

Understand the theory of the z transformation and be able to compute probabilities
using a normal probability distribution. Be able to compute values of variables based
upon probabilities from the normal distribution. Understand the principles of the cumulative normal distribution function.

Sampling distributions and interval estimation:

Understand the importance of sampling and how samples can generate estimates
of population parameters such as mean, standard deviation and/or proportion.

Know what random sampling is and how random samples are selected.

Understand the concept of a sampling distribution and the role of the Central Limit Theorem.

Specifically know the characteristics of the sampling distributions of the sample mean and sample proportion.

Know how to construct and interpret interval estimates of population means and proportions.

Be able to compute, and interpret, the margin of error associated with estimators.

Understand the t distribution and its role in constructing an interval for a population mean.

Be able to determine the size of a random sample necessary to estimate a mean and/or proportion with a specified level of precision.

Hypothesis testing:

Be able to formulate and test hypotheses about population means and proportions.

Understand the concepts of Type I and Type II errors and their relationship to levels of significance.

Know how to compute test statistics and p-values, and how to use critical values to draw conclusions.

Be able to develop interval estimates and conduct hypothesis tests about the difference
between two population means when the samples are independent and when the samples are matched.

Be able to develop interval estimates and conduct hypothesis tests about the difference between the proportions in two populations.

Simple linear regression:

Understand how regression analysis can be used to develop an equation that describes how two variables are related.

Know how to fit an estimated regression equation to sample data based upon
the least squares method. Be able to recognize the key components of the parameter estimators.

Understand the roles of sums of squares in the measurement and decomposition of total variation.

Be able to determine goodness of fit and compute the sample correlation coefficient.

Understand the assumptions necessary for statistical inference and be able to test for a significant relationship with the t and F distributions.

Know how to develop confidence and prediction interval estimates, respectively,
of y given a specific value of x in the cases of a mean value of y and an individual value of y.

Using experimental techniques, in particular true controlled experiments and random sampling
from customer and vendor databases, to test marketing programs such as new customer acquisitions,
cross-sell and upsell programs and customer loyalty and lifetime value enhancement programs.

Customer acquisition tools and techniques combining customer database information
with vendor database information and using multivariate predictive models on experimental
tests to select prospects who will add most to total firm customer lifetime value.

Customer relationship management theory and the management of customer loyalty;
development and testing of loyalty programs.

Target market selection for cross-sell and up-sell using multivariate techniques.